The collaboration marks a turning point in AI-driven drug design and trial forecasting, de-risking the drug development ...
Designing an efficient platform is crucial for any industrial process. This design process is known as process development, and it has become increasingly important in the pharmaceutical industry at ...
A key part of consultants’ work is the global harmonization of CMC guidelines. Differences in regulatory requirements across regions can lead to inefficiencies in the drug development process.
Find out how NAMs are influencing safety assessments and decision-making in the pharmaceutical industry ahead of 2026.
AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...
DALLAS--(BUSINESS WIRE)--Lantern Pharma Inc. (NASDAQ: LTRN), an artificial intelligence (AI) company dedicated to developing cancer therapies and transforming the cost, pace, and timeline of oncology ...
AI in drug discovery offers key market opportunities by enhancing drug development efficiency, reducing costs, and improving success rates. It supports personalized medicine, facilitating custom ...
Researchers have applied AI and machine learning to every stage of the drug development process. This includes identifying targets in the body, screening potential candidates, designing drug molecules ...
Developing high-quality, safe, and effective drugs is a complex process that requires varied scientific skills and stringent regulatory assessments. Drug development is a process that spans many years ...
After its founding in 1976, scientists at Genentech worked methodically toward the development of its first biotechnology product. It was nearly a decade later that the FDA approved Protropin, a ...
To optimize the final formulation for a drug, it must meet many criteria beyond producing a safe and effective product. For example, it must be stable and amenable to various manufacturing steps, such ...
Sherry Gu, Executive Vice President and CTO at WuXi Biologics, explains the critical challenges of developing bispecific ...
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